code: def k_previous_obs(observations, cur_age, k):
      if len(observations) == 0:
          return [-1, -1, -1, -1, -1]
      for i in range(k):
          dt = k - i
          if cur_age - dt in observations:
              return observations[cur_age - dt]
      max_age = max(observations.keys())
      return observations[max_age]
  
file_path: PaddleDetection/ppdet/modeling/mot/tracker/ocsort_tracker.py
imports: import numpy
  from ..matching.ocsort_matching import associate, linear_assignment, iou_batch, associate_only_iou
  from ..motion.ocsort_kalman_filter import OCSORTKalmanFilter
  from ppdet.core.workspace import register, serializable
label_desc: Use image node_id 1 for calling a global function with example usage: k_previous_obs(observations, cur_age, k) and returns: observations, list, observations